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Reevaluation by CRISPR-Cas9 approach reveals multiple lincRNAs dispensable for pluripotency maintenance and SNORA73 essential for pluripotency exit (RNA-Seq)

GSE225237 Mus musculus (mouse) Single-cell RNA-seq 12 samples Submitted 2024/08/07 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 12 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Mus musculus (mouse)
Samples
12 samples: 6 conditions, mostly in duplicateGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper
Reevaluation by the CRISPR/Cas9 knockout approach revealed that multiple pluripotency-associated lncRNAs are dispensable for pluripotency maintenance while Snora73a/b is essential for pluripotency exitScience China. Life sciences · 2024
Summary (written by the submitters)
Many lincRNAs have been identified as essential regulators for ESC pluripotency through siRNA-based screening. However, the biological and molecular functions of the large intergenic noncoding RNAs (lincRNAs) remain unclear. Here, we employed CRISPR/Cas9-mediated knockout technology to explore the functions of 8 previously annotated lincRNAs in ESCs.
Read the full summary ↓
Unexpectedly, it was found that most lincRNAs are dispensable for pluripotency maintenance, cloning formation ability, proliferation and apoptosis in ESCs when we disrupted these lincRNAs individually or in combinations. Single-cell transcriptomic analysis of a set of lncRNA knockout ESCs showed consistent results, indicating that previously observed functions of lincRNAs on ESC pluripotency maintenance may be due to off-targeted effects. Interestingly, deletion and transcriptional repression of linc1343 disrupts embryoid body (EB) differentiation in ESC. Notably, GM17300 and two small RNAs (Snora73a, Snora73b) derived from the lnc1343 locus are highly expressed in ESCs. Further overexpression of Snora73a and Snora73b in linc1343 knockout cells rescue the phenotype, suggesting that snoRNAs derived from linc1343 are the responders for EB differentiation. Taken together, our results demonstrate the divergent effects of lincRNAs on regulating ESC pluripotency and EB differentiation.
Published in
Reevaluation by the CRISPR/Cas9 knockout approach revealed that multiple pluripotency-associated lncRNAs are dispensable for pluripotency maintenance while Snora73a/b is essential for pluripotency exit
Li Z, Li X, Lin J et al. · Science China. Life sciences 2024 · PMID 38995489 · doi:10.1007/s11427-023-2594-3
This dataset
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE225237_RAW.tar (it can run to tens of gigabytes).

3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

What the files usually look like: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA934460 and SRA study SRP422612. Searching any of these in the dataset finder brings you back here.

Study design
6 conditions, mostly in duplicate
WT+1343KO-a14-D0 ×2 WT+1343KO-a14-D8 ×2 WT+1343KO-a14-D16 ×2 WT-D0 ×2 WT-D8 ×2 WT-D16 ×2

Supports a between-group comparison across 12 samples.

How we read this: 6 replicated groups read from 12 sample titles; they account for 12 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study
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